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PhD position: Artificial Intelligence for advanced acute ischemic stroke image analysis

Apply before: 25 September 2020
Working time: Day
Working hours: 36 hours per week
Discipline: AMC Medical Research (AMR)
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What you are going to do

Our goal will be to develop methods to optimize the workflow of treatment of patients using advanced AI. To achieve this, we will develop, implement and validate novel AI-based computer vision algorithms for the support of treatment decision and prognostic estimations of patients suffering from an acute ischemic stroke. This research will be embedded in a multidisciplinary team of researchers with a background in Medicine, Biomedical Engineering, AI, Technical Medicine, physics, and computer science. For this project we seek for 3 PhD students, one with a (technical) Medicine background, one with applied AI and medical image analysis background, and one with a theoretical AI background. Specific tasks of the AI candidates include (1) study deep neural networks for spatiotemporal segmentation and tracking in long and complex sequences applied to CT scans, (2) synthesis of dynamic series using a limited number of time snapshots, (3) develop approaches to deal with high-dimensionality low sample size applications, (4) evaluate clinical value in treatment decision support for patients suffering from an acute ischemic stroke, and (5) perform novel academic research on computer vision, deep machine learning, and medical imaging.

We are looking for two candidates for the PhD position.

What we expect from you

We are looking for a candidate with a MSc degree in Computer Science, AI, (applied) Mathematics, (applied) Physics, biomedical engineering, or a related field. Affinity with image and signal analysis and programming are essential. The candidate is able to combine programming skills with analytical insights. Moreover, the candidate should have the ability to work in a multidisciplinary research group in order to bridge the gap between the clinic, biomedical engineering research and computer science lab.

Where you are going to work

The AIRBORNE project, which stands for Artificial Intelligence for early imaging Based patient selection in acute ischemic stRoke, is aimed at developing and validating new radiological imaging  biomarkers that support treatment decision support for patients suffering from an acute ischemic stroke. AIRBORNE is a collaboration of the Amsterdam UMC, the University of Amsterdam, and Nico.lab. Within the project, the PhD candidate will be working in strong collaboration of the Department of Biomedical Engineering & Physics and the Department of Radiology and Nuclear Medicine of the Amsterdam UMC and the AI lab of the Computer Vision department of the UvA. The Amsterdam UMC are amongst the world leaders in imaging processing for acute ischemic stroke, whereas the UvA is world leading in AI-based computer vision of video images. The candidate will participate in a truly-multi-disciplinary team of stroke researchers varying from medical researchers to physicists and from computer scientist to biomedical engineers. See also www.qia.amsterdam. .

What we offer you

We offer you ample opportunity for development, deepening and broadening, additional training and a place to grow! Working at AMR means working in an inspiring and professional environment where development is encouraged in every respect.

  • The maximum gross monthly salary based on a 36-hour work week is € 3.196,- (scale 21 CAO UMC). 
  • The base salary does not include holiday pay (8%) and a year-end bonus (8.3%). 
  • We offer a contract for 48 months.
  • In addition to excellent accessibility by public transport, AMC also has a sufficient number of parking spaces for employees.
  • Pension is accrued at Be Frank.

For an overview of all our other terms of employment, see https://werkenbijamc.nl/arbeidsvoorwaarden-amr/

Let’s meet

If you would like to apply directly, please use the ‘apply’ button on this page.
If you would like more information, please feel free to contact Henk Marquering (Associate Professor), via h.a.marquering@amsterdamumc.nl or contact Efstratios Gavves (Assistant Professor), via egavves@uva.nl.

We look forward to meeting you!

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